From d717eb079cd6b7fa7a4f97c0a10d400bdec753fb Mon Sep 17 00:00:00 2001 From: Greg Fuller Date: Tue, 11 Oct 2022 18:02:41 -0700 Subject: [PATCH] Interrogate: add option to include ranks in output Since the UI also allows users to specify ranks, it can be useful to show people what ranks are being returned by interrogate This can also give much better results when feeding the interrogate results back into either img2img or txt2img, especially when trying to generate a specific character or scene for which you have a similar concept image Testing Steps: Launch Webui with command line arg: --deepdanbooru Navigate to img2img tab, use interrogate DeepBooru, verify tags appears as before. Use "Interrogate CLIP", verify prompt appears as before Navigate to Settings tab, enable new option, click "apply settings" Navigate to img2img, Interrogate DeepBooru again, verify that weights appear and are properly formatted. Note that "Interrogate CLIP" prompt is still unchanged In my testing, this change has no effect to "Interrogate CLIP", as it seems to generate a sentence-structured caption, and not a set of tags. (reproduce changes from https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2149/commits/6ed4faac46c45ca7353f228aca9b436bbaba7bc7) --- modules/deepbooru.py | 14 +++++++++----- modules/interrogate.py | 7 +++++-- modules/shared.py | 1 + modules/ui.py | 5 ++--- 4 files changed, 17 insertions(+), 10 deletions(-) diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 7e3c06182..32d741e20 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -3,7 +3,7 @@ from concurrent.futures import ProcessPoolExecutor from multiprocessing import get_context -def _load_tf_and_return_tags(pil_image, threshold): +def _load_tf_and_return_tags(pil_image, threshold, include_ranks): import deepdanbooru as dd import tensorflow as tf import numpy as np @@ -52,12 +52,16 @@ def _load_tf_and_return_tags(pil_image, threshold): if result_dict[tag] >= threshold: if tag.startswith("rating:"): continue - result_tags_out.append(tag) + tag_formatted = tag.replace('_', ' ').replace(':', ' ') + if include_ranks: + result_tags_out.append(f'({tag_formatted}:{result_dict[tag]})') + else: + result_tags_out.append(tag_formatted) result_tags_print.append(f'{result_dict[tag]} {tag}') print('\n'.join(sorted(result_tags_print, reverse=True))) - return ', '.join(result_tags_out).replace('_', ' ').replace(':', ' ') + return ', '.join(result_tags_out) def subprocess_init_no_cuda(): @@ -65,9 +69,9 @@ def subprocess_init_no_cuda(): os.environ["CUDA_VISIBLE_DEVICES"] = "-1" -def get_deepbooru_tags(pil_image, threshold=0.5): +def get_deepbooru_tags(pil_image, threshold=0.5, include_ranks=False): context = get_context('spawn') with ProcessPoolExecutor(initializer=subprocess_init_no_cuda, mp_context=context) as executor: - f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, ) + f = executor.submit(_load_tf_and_return_tags, pil_image, threshold, include_ranks) ret = f.result() # will rethrow any exceptions return ret \ No newline at end of file diff --git a/modules/interrogate.py b/modules/interrogate.py index 635e266e7..af858cc09 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -123,7 +123,7 @@ class InterrogateModels: return caption[0] - def interrogate(self, pil_image): + def interrogate(self, pil_image, include_ranks=False): res = None try: @@ -156,7 +156,10 @@ class InterrogateModels: for name, topn, items in self.categories: matches = self.rank(image_features, items, top_count=topn) for match, score in matches: - res += ", " + match + if include_ranks: + res += ", " + match + else: + res += f", ({match}:{score})" except Exception: print(f"Error interrogating", file=sys.stderr) diff --git a/modules/shared.py b/modules/shared.py index c1092ff79..3e0bfd726 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -251,6 +251,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { options_templates.update(options_section(('interrogate', "Interrogate Options"), { "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"), "interrogate_use_builtin_artists": OptionInfo(True, "Interrogate: use artists from artists.csv"), + "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."), "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), diff --git a/modules/ui.py b/modules/ui.py index 1204eef7b..f4dbe2472 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -311,13 +311,12 @@ def apply_styles(prompt, prompt_neg, style1_name, style2_name): def interrogate(image): - prompt = shared.interrogator.interrogate(image) - + prompt = shared.interrogator.interrogate(image, include_ranks=opts.interrogate_return_ranks) return gr_show(True) if prompt is None else prompt def interrogate_deepbooru(image): - prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold) + prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold, opts.interrogate_return_ranks) return gr_show(True) if prompt is None else prompt